摘要
针对论坛文档由于自身特点缺乏有效的文档摘要方法的现状,提出一种基于LDA主题模型的论坛文档摘要方法.在主题建模中考虑了Web论坛文档中帖子和帖子之间的回复关系,并把主题的分布变为随文档变化而变化的一个动态过程,来解决主题的依赖和偏移问题.在使用GibbsEM采样算法来确定动态主题模型的参数后,通过计算句子中主题权重之和来确定各个主题的重要程度;最后根据动态主题模型中主题的概率分布计算各句子的权重并得到文档的摘要.实验结果表明,新方法在各个ROUGE评测标准上均优于其他各种对比的摘要方法.
Because there is no effective document summarization method for Web forum threads currently, this paper proposes a Web forums thread summarization method based on a latent Dirichlet allocation （LDA） topic model. To handle the topic dependencies and the drifting problem, we consider the reply-relations among posts in topic modeling, and set the distribution of each topic as a dynamic process with the change of the thread discussion. We utilize the Gibbs EM algorithm to get parameters of the proposed dynamic topic model and determine the importance of each topic according to the sum of the topic weight over all sentences. Finally we calculate the scores of sentences based on probability distribution of topics and then generate the summarization of each thread. The experimental results on the two different forum data sets show that the new method outperforms several widely used summarization methods in terms of ROUGE metrics.
出处
《计算机研究与发展》
EI
CSCD
北大核心
2012年第11期2359-2367,共9页
Journal of Computer Research and Development
基金
国家自然科学基金项目(60970047
61103151
61173068)
山东省自然科学基金项目(ZR2012FM037)
